Visualisation

import pandas as pd
df = pd.read_csv('covid_19_data.csv',parse_dates=['Last Update'],index_col=0) 
#parsing according to the last update datetime column
#serial number as index
df.rename(columns={'ObservationDate':'Date', 'Country/Region':'Country'}, inplace=True)
#renaming certain columns

#used for Map later
df_confirmed = pd.read_csv("time_series_covid_19_confirmed.csv")
df_confirmed.rename(columns={'Country/Region':'Country'}, inplace=True)
df_confirmed = df_confirmed[["Province/State","Lat","Long","Country"]]
df_temp = df.copy()
df_temp['Country'].replace({'Mainland China': 'China'}, inplace=True)
df_latlong = pd.merge(df_temp, df_confirmed, on=["Country", "Province/State"])

confirmed = df.groupby('Date').sum()['Confirmed'].reset_index()
deaths = df.groupby('Date').sum()['Deaths'].reset_index()
recovered = df.groupby('Date').sum()['Recovered'].reset_index()

import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Bar(x=confirmed['Date'],
                y=confirmed['Confirmed'],
                name='Confirmed',
                marker_color='blue'
                ))
fig.add_trace(go.Bar(x=deaths['Date'],
                y=deaths['Deaths'],
                name='Deaths',
                marker_color='Red'
                ))
fig.add_trace(go.Bar(x=recovered['Date'],
                y=recovered['Recovered'],
                name='Recovered',
                marker_color='Green'
                ))

fig.update_layout(title='Worldwide Corona Virus Cases - Confirmed, Deaths, Recovered (Bar Chart)',
    xaxis_tickfont_size=14,
    yaxis=dict(
        title='Number of Cases',
        titlefont_size=16,
        tickfont_size=14,
    ),
    legend=dict(
        x=0,
        y=1.0,
        bgcolor='rgba(255, 255, 255, 0)',
        bordercolor='rgba(255, 255, 255, 0)'
    ),
    barmode='group',
    bargap=0.15, # gap between bars of adjacent location coordinates.
    bargroupgap=0.1 # gap between bars of the same location coordinate.
)
fig.show()
#steep rise in confirmed cases around 12th March 2020. Reason could be more tests and results 
#available 

df_grouped = df.groupby('Country')['Confirmed', 'Deaths', 'Recovered'].sum().reset_index()
n = 5
c_lrgst = df_grouped.Confirmed.nlargest(n)
d_lrgst = df_grouped.Deaths.nlargest(n)
r_lrgst = df.Recovered.nlargest(n)

top_5 = df_grouped.query('Confirmed in @c_lrgst')

fig = go.Figure()   
fig.add_trace(go.Scatter(x=top_5['Country'], 
                         y=top_5['Confirmed'],
                         mode='lines+markers',
                         name='Confirmed',
                         line=dict(color='blue', width=2)
                        ))
fig.add_trace(go.Scatter(x=top_5['Country'], 
                         y=top_5['Deaths'],
                         mode='lines+markers',
                         name='Deaths',
                         line=dict(color='Red', width=2)
                        ))
fig.add_trace(go.Scatter(x=top_5['Country'], 
                         y=top_5['Recovered'],
                         mode='lines+markers',
                         name='Recovered',
                         line=dict(color='Green', width=2)
                        ))
fig.update_layout(
    title='Top 5 Countries with Corona Virus Cases (Line Chart)',
    xaxis_tickfont_size=14,
    yaxis=dict(
        title='Number of Cases',
        titlefont_size=16,
        tickfont_size=14,
    ),
    legend=dict(
        x=0,
        y=1.0,
        bgcolor='rgba(255, 255, 255, 0)',
        bordercolor='rgba(255, 255, 255, 0)'
    )
)
fig.show()
#China cases far more than the other top 5 countries

import plotly.graph_objects as go
import numpy as np
China = df.query('Country=="Mainland China"').groupby("Last Update")[['Confirmed', 'Deaths', 'Recovered']].sum().reset_index()
z = np.random.poisson(size=(len(China['Confirmed']), len(China['Last Update'])))

fig = go.Figure(data=go.Heatmap(
        z=z,
        x=China['Last Update'],
        y=China['Confirmed'],
        colorscale='fall'))

fig.update_layout(
    title='China - Number of Cases per day',
    xaxis_nticks=5)

fig.show()

#Cases are still increasing . No notion of decrease till now.

import plotly.express as px
fig = px.density_mapbox(df_latlong, 
                        lat="Lat", 
                        lon="Long", 
                        hover_name="Province/State", 
                        hover_data=["Confirmed","Deaths","Recovered"], 
                        animation_frame="Date",
                        color_continuous_scale="Portland",
                        radius=7, 
                        zoom=1,height=700)
fig.update_layout(title='Worldwide Corona Virus Cases Time Lapse - Confirmed, Deaths, Recovered',
                  font=dict(family="Courier New, monospace",
                            size=14,
                            color="#7f7f7f")
                 )
fig.update_layout(mapbox_style="open-street-map", mapbox_center_lon=0)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0}) #tight layout - right , top, left , below


fig.show()
#trend of spread and at what rate. Huge jump in March